Onfleet MCP Server for Vercel AI SDK 10 tools — connect in under 2 minutes
The Vercel AI SDK is the TypeScript toolkit for building AI-powered applications. Connect Onfleet through Vinkius and every tool is available as a typed function. ready for React Server Components, API routes, or any Node.js backend.
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Vinkius supports streamable HTTP and SSE.
import { createMCPClient } from "@ai-sdk/mcp";
import { generateText } from "ai";
import { openai } from "@ai-sdk/openai";
async function main() {
const mcpClient = await createMCPClient({
transport: {
type: "http",
// Your Vinkius token. get it at cloud.vinkius.com
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
});
try {
const tools = await mcpClient.tools();
const { text } = await generateText({
model: openai("gpt-4o"),
tools,
prompt: "Using Onfleet, list all available capabilities.",
});
console.log(text);
} finally {
await mcpClient.close();
}
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Onfleet MCP Server
Connect your Onfleet delivery operations to any AI agent and run your fleet from a single conversation.
The Vercel AI SDK gives every Onfleet tool full TypeScript type inference, IDE autocomplete, and compile-time error checking. Connect 10 tools through Vinkius and stream results progressively to React, Svelte, or Vue components. works on Edge Functions, Cloudflare Workers, and any Node.js runtime.
What you can do
- Delivery Tasks — Create, update, delete, and force-complete delivery tasks with full address and recipient details
- Fleet Tracking — List all active drivers, check who's online, and view their assigned capacities in real time
- Driver Schedules — Pull exact shift times and availability windows for any worker in your fleet
- Teams & Hubs — Browse your team structure and dispatch hubs with geographic coordinates and zone coverage
- Task History — Query tasks by date range to audit completed, failed, or pending deliveries across your operation
The Onfleet MCP Server exposes 10 tools through the Vinkius. Connect it to Vercel AI SDK in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Onfleet to Vercel AI SDK via MCP
Follow these steps to integrate the Onfleet MCP Server with Vercel AI SDK.
Install dependencies
Run npm install @ai-sdk/mcp ai @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the script
Save to agent.ts and run with npx tsx agent.ts
Explore tools
The SDK discovers 10 tools from Onfleet and passes them to the LLM
Why Use Vercel AI SDK with the Onfleet MCP Server
Vercel AI SDK provides unique advantages when paired with Onfleet through the Model Context Protocol.
TypeScript-first: every MCP tool gets full type inference, IDE autocomplete, and compile-time error checking out of the box
Framework-agnostic core works with Next.js, Nuxt, SvelteKit, or any Node.js runtime. same Onfleet integration everywhere
Built-in streaming UI primitives let you display Onfleet tool results progressively in React, Svelte, or Vue components
Edge-compatible: the AI SDK runs on Vercel Edge Functions, Cloudflare Workers, and other edge runtimes for minimal latency
Onfleet + Vercel AI SDK Use Cases
Practical scenarios where Vercel AI SDK combined with the Onfleet MCP Server delivers measurable value.
AI-powered web apps: build dashboards that query Onfleet in real-time and stream results to the UI with zero loading states
API backends: create serverless endpoints that orchestrate Onfleet tools and return structured JSON responses to any frontend
Chatbots with tool use: embed Onfleet capabilities into conversational interfaces with streaming responses and tool call visibility
Internal tools: build admin panels where team members interact with Onfleet through natural language queries
Onfleet MCP Tools for Vercel AI SDK (10)
These 10 tools become available when you connect Onfleet to Vercel AI SDK via MCP:
complete_task_override
Force-complete a delivery task
create_delivery_task
Create a new delivery task in Onfleet
delete_delivery_task
Delete/Archive a delivery task
get_task_details
Get details for a specific delivery task
get_worker_schedule
Get a driver's work schedule
list_dispatch_hubs
List all dispatch hubs
list_fleet_teams
List all delivery teams
list_fleet_workers
List all fleet drivers/workers
list_tasks_by_date
List delivery tasks within a date range
update_delivery_task
Update an existing delivery task
Example Prompts for Onfleet in Vercel AI SDK
Ready-to-use prompts you can give your Vercel AI SDK agent to start working with Onfleet immediately.
"Create a delivery task to 123 Main St, San Francisco for John Doe with phone 415-555-0100."
"Show me all deliveries from yesterday with their status."
"Which drivers are online right now and how many active tasks does each have?"
Troubleshooting Onfleet MCP Server with Vercel AI SDK
Common issues when connecting Onfleet to Vercel AI SDK through the Vinkius, and how to resolve them.
createMCPClient is not a function
npm install @ai-sdk/mcpOnfleet + Vercel AI SDK FAQ
Common questions about integrating Onfleet MCP Server with Vercel AI SDK.
How does the Vercel AI SDK connect to MCP servers?
createMCPClient from @ai-sdk/mcp and pass the server URL. The SDK discovers all tools and provides typed TypeScript interfaces for each one.Can I use MCP tools in Edge Functions?
Does it support streaming tool results?
useChat and streamText that handle tool calls and display results progressively in the UI.Connect Onfleet with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Onfleet to Vercel AI SDK
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.